There are generally two ways to solve a recognition task as it relates to image detection. A first method is semantic segmentation. In semantic segmentation, a pre-defined class label is associated with each pixel in an image. The image is segmented into regions comprising the various objects defined by the class labels. In some examples, pixels can be classified with respect to their local features, such as color or texture. Another method to solve a recognition task is to use object detection. In object detection, bounding rectangles or boxes are used to segment objects from one another. In image recognition, a bounding box can be considered the smallest enclosing box within which all pixels of an object lie.